International Society of Oncology Pharmacy Practitioners global position on the use of biosimilars in cancer treatment and supportive care
Bibliographic record
Abstract
With the development of innovative cancer treatments over recent decades, the cost of cancer care has risen exponentially, limiting patient access to patented originator biotherapeutics in many countries. The introduction of biosimilars to the market has created new opportunities as well the need for changes in practice within healthcare institutions. A ‘biosimilar’ is a biotherapeutic product which is highly similar in terms of quality, safety and efficacy to an already licensed originator product. Although biosimilars lack clinically meaningful differences in therapeutic activity as compared to the originator product, these complex biological molecules are not considered identical chemical copies, unlike generics, and minor differences in molecular structure and inactive compounds may exist. A thorough understanding of these differences and their clinical implications is necessary for optimising medicines-use practices involving biosimilars. This position statement, developed by the International Society of Oncology Pharmacy Practitioners Biosimilars Taskforce, aims to provide the global oncology pharmacy community with guidance to support decisions around biosimilar use. The 11 statements cover the regulation and evaluation of biosimilars, practical issues around local implementation, the education of healthcare staff and patients, and the requirement for ongoing pharmacovigilance and outcome monitoring.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.036 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.023 | 0.022 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".